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IEEE International Conference on Web Services (ICWS)

作者： Haojuan Zhang Yali Wang Peiyan Yuan Junna Zhang College of Computer and Information Engineering Henan Normal University Xinxiang China College of Computing Science and Artificial Intelligence Suzhou City University Suzhou China

ISBN: (数字)9798350368550

ISBN: (纸本)9798350368567

As the size of data clusters grows, the issues of storage redundancy, data availability, and the cost of edge caching systems become the focus of attention. Although the multi-copy strategy improves data availability, its redundancy cost is high and does not fully consider file data characteristics. Erasure codes techniques have been widely studied as an alternative, but the selection of a suitable coding scheme remains a challenge. To this end, we propose a hybrid coding caching scheme. Firstly, we predict data types using machine learning methods to ensure that the most valuable content is stored. Secondly, for the characteristics of the multi-copy strategy, low-density parity check (LDPC), and Reed-Solomon coding (RS), we propose an adaptive data partitioning strategy (ADPRF) to select appropriate coding schemes for different data. Finally, by combining the ideas of dynamic programming and heuristic algorithms, we propose a redundancy-aware edge collaborative caching algorithm (RPCO) with joint optimization of energy and cost to determine the optimal set of collaborative nodes and the optimal cache locations for files. Compared with the traditional responsive caching scheme, this algorithm can reduce the system cost by 13.8% and access latency by 11.5%.

关键词： Costs Web services Heuristic algorithms Redundancy Collaboration Encoding Parity check codes partitioning algorithms Dynamic programming Optimization

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Faster algorithms for a Lexicographic Bi-Criteria Line Balancing Problem with Totally Ordered Precedence Constraints

Faster Algorithms for a Lexicographic Bi-Criteria Line Balan...

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International Symposium on Soft Computing and Intelligent Systems (SCIS)

作者： Shinji Imahori Yoshiyuki Karuno Yuma Ueda Faculty of Science and Engineering Chuo University Tokyo Japan Faculty of Mechanical Engineering Kyoto Institute of Technology Kyoto Japan Mechanodesign Program Graduate School of Science and Technology Kyoto Institute of Technology Kyoto Japan

ISBN: (数字)9798350373332

ISBN: (纸本)9798350373349

The line balancing has been an important production strategy which aims at redressing the balance of workloads on machines in an assembly type of production system. In this paper, a lexicographic bi-criteria optimization model of the line balancing is revisited for a mass-production of one homogeneous product. A sequence of machines and a totally ordered set of tasks are given. The machines are considered to be situated along with a production line, according to their sequence. Precedence relations between tasks are specified by the total order of tasks. The task set also consists of a given number of disjoint subsets, namely categories such that tasks in a category are considered to constitute a certain kind of family of technical skills. Each task has a positive processing time and a category index. A solution to the problem is expressed by an assignment of tasks to machines, and for the feasibility of a solution, the assignment must obey the totally ordered precedence constraint on tasks. The sum of processing times of tasks assigned to a machine in a feasible solution is the load of the machine, and the number of category indexes of tasks assigned to a machine is referred to as the degree of diverseness of the task subset. The primary objective of the problem is to minimize the maximum machine load, and the second objective is to minimize the maximum degree of diverseness of tasks assigned to a machine. The lexicographic bi-criteria line balancing problem with totally ordered precedence constraints has been known to admit a polynomial time exact algorithm, whose time complexity is linear in the number of machines and squared in the number of tasks. In this paper, a faster polynomial time exact algorithm is proposed, which improves the time complexity to be squared in the number of tasks.

关键词： Production systems Heuristic algorithms Optimization models Polynomials partitioning algorithms Complexity theory Indexes Time complexity Assembly Sorting

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Handling Latch Loops in Timing Analysis with Improved Complexity and Divergent Loop Detection

Handling Latch Loops in Timing Analysis with Improved Comple...

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Design, Automation and Test in Europe Conference and Exhibition

作者： Xizhe Shil Zizheng Guo Yibo Lin Runsheng Wang Ru Huang School of Integrated Circuits Peking University Institute of Electronic Design Automation Peking University Beijing Advanced Innovation Center for Integrated Circuits

ISBN: (数字)9783982674100

ISBN: (纸本)9798331534646

Latch loops introduce feedback cycles in timing graphs for static timing analysis (STA), disrupting timing propagation in topological order. Existing timers handle latch loops by checking the convergence of global iterations in timing propagation without lookahead detection of divergent loops. Such a strategy ends up with the worst-case runtime complexity $O(n^{2})$ , where n is the number of pins in the timing graph. This can be extremely time-consuming, when n goes to millions and beyond. In this paper, we address this challenge by proposing a new algorithm consisting of two steps. First, we identify the strongly connected components (SCCs) and levelize them into different stages. Second, we implement parallelized arrival time (AT) propagation between SCCs while conducting sequential iterations inside each SCC. This strategy significantly reduces the runtime complexity to $O\left(\sum_i k_i^2\right)$ from the previous global propagation, where $k_{i}$ is the number of pins in each SCC. Our timer also detects timing information divergent loops in advance, avoiding over-iteration. Experimental results on industrial designs demonstrate 10.31× and 8.77× speed-up over PrimeTime and OpenSTA on average, respectively.

关键词： Latches Runtime Circuits Europe Timing Complexity theory Pins partitioning algorithms Convergence

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Towards Efficient K-Dominant Skyline Computation in CSCW

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Chinese Journal of Electronics 2023年第3期21卷 445-448页

作者： Jin HUANG Jian CHEN Da HUANG Yong TANG School of Computer Science South China Normal University Guangzhou China School of Software Engineering South China University of Technology Guangzhou China School of Computing Science Simon Fraser University Burnaby BC Canada

Considering benefits of different collaborators, cooperative work usually faces the challenge to make a trade-off decision upon multiple criterions. K-dominant skyline, a novel database query technology, may return appropriate optimal choices and play as a solution. To reduce intensive comparisons between objects in skyline computation, we propose a novel sorting-based algorithm named Sorted cumulative algorithm. Furthermore, to meet the requirement of distributed collaborative environment, we also address Parallel SCA, which accelerates the computation based on some data partitioning techniques. Extensive experiments are conducted to confirm the superior efficiency of the proposed methods against existing ones, especially in the context of high dimensional datasets.

关键词： Federated learning Distributed databases Collaboration Load management partitioning algorithms Computational efficiency Faces

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MTRP: A High-Performance Cost-Efficient Buffering Scheme for Multi-Tenant Cloud Services

MTRP: A High-Performance Cost-Efficient Buffering Scheme for...

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International Symposium on Parallel and Distributed Processing with Applications, ISPA

作者： Zekai Zhu Peiquan Jin Guorui Huang Xiaoliang Wang Yigui Yuan University of Science and Technology of China Hefei China Unit 31002 the Chinese People’s Liberation Army Beijing China

ISBN: (数字)9798331509712

ISBN: (纸本)9798331509729

Multi-tenancy is a crucial criterion for cloud service providers since it enables them to share resources among tenants, thus reducing costs. As all tenants share the same buffer space in the cloud server, a tenant’s overall performance will be affected by other tenants. Thus, developing an efficient buffering scheme to ensure tenant isolation becomes an urgent need. Aiming to solve this problem, this paper proposes a novel buffering scheme for managing the shared buffer in a multi-tenant cloud database. We first present an SLA (Service Level Agreement)-based model to quantify the buffering performance of each tenant. Then, we propose MTRP (Multi-Tenant Replacement Policy) for multi-tenant scenarios. The novelty of MTRP lies in three aspects: (1) it partitions the buffer into logical zones to implement tenant isolation. Each zone manages the pages one tenant uses, but the zone space can be dynamically adjusted by buffer replacements; (2) it proposes a two-step replacement algorithm, including global replacement and local replacement, which can improve space efficiency and reduce the SLA cost; (3) it adopts a reinforcement learning model to select the most appropriate zone for page replacement. The experimental results on various multi-tenant workloads show that MTRP achieves a higher hit ratio and lower SLA costs than LRU, LFU, LRU-2, and LeCaR.

关键词： Distributed processing Costs Databases Heuristic algorithms Reinforcement learning Minimization partitioning algorithms Servers History Service level agreements

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A Split-Merging K-Means Clustering Algorithm with User Attributes for Collaborative Filtering

A Split-Merging K-Means Clustering Algorithm with User Attri...

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International Conference on Communications and Electronics, ICCE

作者： Dang Thi Nuong Nguyen Xuan Dung Phuong Xuan Quang Vinh Tran-Quang Hanoi University of Science and Technology Hanoi Vietnam

ISBN: (数字)9798350379792

ISBN: (纸本)9798350379808

Collaborative Filtering (CF) stands out as a robust recommendation method that can significantly improve the accuracy of the recommendation system. Nevertheless, conventional CF algorithms face challenges such as cold start and data sparsity. This study presents an approach that combines a split-merging clustering algorithm with user attributes to improve CF performance. Initially, the Split-Merging Clustering (SMKC) algorithm is utilized to cluster users based on their rating vectors, resulting in SMKC. Subsequently, the similarity of the user is calculated by integrating attributes such as age, gender, and occupation to identify the nearest neighbors. Finally, item evaluations are predicted based on user similarities within the nearest-neighbor set to generate the list of recommendations. Experimental findings demonstrate that the proposed method outperforms traditional approaches in generating recommendation lists, addressing issues related to data sparsity and the inherent cold start in the data.

关键词： Filtering Collaborative filtering Clustering algorithms Filtering algorithms Prediction algorithms Vectors partitioning algorithms

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Rule-Based Constraint Elicitation For Active Constraint-Incremental Clustering

Rule-Based Constraint Elicitation For Active Constraint-Incr...

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International Conference on Tools for Artificial Intelligence (ICTAI)

作者： Aymeric Beauchamp Thi-Bich-Hanh Dao Samir Loudni Christel Vrain LIFO EA 4022 University of Orléans INSA Centre-Val-de-Loire Orléans France TASC (LS2N-CNRS) / GREYC IMT Atlantique / University of Caen Normandy Nantes France

ISBN: (数字)9798331527235

ISBN: (纸本)9798331527242

Constrained clustering algorithms integrate user knowledge as constraints in the clustering process to guide it towards a desired outcome. When interacting with users, it is essential to quickly ask simple questions to identify informative constraints that will efficiently enhance an initial partition. We propose a new active query strategy for incremental clustering that translates user feedback into interpretable decision rules and identifies relevant points for queries using rule-based heuristics Experiments on benchmark datasets highlight the benefits of our new approach, making it suitable for real-world applications.

关键词： Clustering algorithms Benchmark testing partitioning algorithms Artificial intelligence

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Opportunistic Network Routing Based on Node Sociality and Location Information

Opportunistic Network Routing Based on Node Sociality and Lo...

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International Conference on Computer Supported Cooperative Work in Design

作者： Gaofeng Zhang Jia Hao Gang Xu Xing Wang Yanhe Fu Ru Yi College of Computer Science Inner Mongolia University Hohhot China

ISBN: (数字)9798350349184

ISBN: (纸本)9798350349191

Opportunistic network nodes exhibit social attributes, and existing community routing algorithms are currently designed for situations where the community structure remains fixed and do not comprehensively analyze the impact of node location information on data forwarding. Over time, the community division results do not match the current network topology structure, and it becomes challenging to select appropriate relay nodes for forwarding. In order to solve this problem, this paper proposes a community routing based on node location information-CRLI. Firstly, the communities are partitioned based on node interaction information, and then the regional affiliation and regional connectivity are defined. Based on these, the CRLI algorithm is designed to comprehensively analyze the influence of node location, movement direction, and dynamic changes in community structure on data forwarding. The experimental results show that the CRLI algorithm can effectively improve the message delivery rate and reduce overhead.

关键词： Epidemics Network topology Federated learning Heuristic algorithms Routing partitioning algorithms Relays

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HW/SW Co-Design of the Secure Hash Function SHA-256

HW/SW Co-Design of the Secure Hash Function SHA-256

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International Conference on Advanced Electrical Engineering (ICAEE)

作者： M. Issad N. Anane N. Guenfoud M. Debyeche Centre de Développement des Technologies Avancées CDTA Alger Algérie Université des Sciences et Technologies Houari Boumediene Bab Ezzouar

ISBN: (数字)9798350349351

ISBN: (纸本)9798350349368

Technological developments in data communication has increased the integration cryptographic algorithms. Hash functions are used in many security schemes such as digital signature/verification and block chain network. Secure Hash Algorithm-256 (SHA-256) is an irreversible hash function. Its algorithm is not only fast, but also provides a high security service. However, in terms of computations complexity, it requires a huge amount of arithmetic operations. This paper presents the implementation of SHA-256 core in reconfigurable FPGA circuit. Our work is based on Programmable System on Chip (PSoC) architecture. The Xilinx Microblaze processor is used for the system flexibility. The SHA-256 algorithm is composed by two steps, namely, the padding operation and the hash computation process to produce the 256-bit message digest. The proposed Hardware/Software (HW /SW) partitioning consists in the execution of the padding step in SW whereas the hash computation is implemented in HW within the SHA-256 core. The implementation results on Virtex-5 circuit show that a 512-bit message digest runs in 2.083 us. The PSoC hardware architecture requires 4058 Slices.

关键词： Hash functions Electrical engineering Computer architecture Hardware System-on-chip partitioning algorithms Blockchains Data communication Computational complexity Field programmable gate arrays

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Blockchain Protocols for Reducing the Proportion of Cross-Shard Transactions

Blockchain Protocols for Reducing the Proportion of Cross-Sh...

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Computer Science and Blockchain (CCSB), International Conference on

作者： Huaizhou Yang Pei Huang Xintian Zhang Department of Computer Science Xi'an Shiyou University Xi’an Shaanxi China Department of Electronic Information Xi'an Shiyou University Xi'an Shaanxi China

ISBN: (数字)9798350356502

ISBN: (纸本)9798350356519

As an effective solution to the blockchain scalability problem, sharding algorithms are widely regarded as having great potential and application prospects. However, the increase in the number of shards naturally gives rise to a series of problems, such as the increase in the proportion of cross-shard transactions, longer transaction confirmation latency, and limited throughput. Therefore, we propose Brockerchain protocol to solve such problems. The protocol uses the convergent louvain algorithm (C-Iouvain) for node partitioning, which balances the load between shards, and then introduces the Agent Account mechanism, which reduces the proportion of cross-shard transactions. Experiments show that this protocol effectively reduces the proportion of inter-shard transactions, improves throughput, and reduces the transaction delay of inter-shard transactions.

关键词： Computer science Sharding Protocols Scalability Throughput Load management Blockchains partitioning algorithms Delays

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